As a Senior AI Engineer at PoliceAI, you will lead the design, development, and deployment of AI-enabled products, translating policing needs into technical solutions. You will work with multidisciplinary teams to build secure, maintainable, and scalable services, and support the testing, evaluation, and validation of AI products.
As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.
This role involves developing and maintaining production-grade Python services for Generative AI and RAG solutions. Responsibilities include building and integrating LLM workflows, implementing retrieval and evidence processing, and optimizing response quality and performance.
This role involves developing, testing, and maintaining Python software for defence cloud integration. Responsibilities include contributing to data and AI projects, automation, DevOps, and infrastructure, while working with tools like Red Hat OpenShift, HashiCorp Vault, and Tekton Pipelines.
This role involves designing and developing Python backend services and APIs using FastAPI, building Generative AI and Agentic AI applications, and integrating LLMs with enterprise applications. You will work with AWS services, CI/CD pipelines, and collaborate with experienced AI engineers and architects to deliver secure, scalable AI solutions.
SENIOR PYTHON SOFTWARE ENGINEER - SC / DV CLEAREDNEW PERMANENT OPPORTUNITY AVAILABLESalary: Up to £100,000 baseLocation: LondonWorking Pattern: Hybrid - 2-4 days per week on-siteClearance: Active SC or DVType: PermanentI'm currently working with an organisation delivering innovative AI and software...
This role involves developing and enhancing AI-driven document processing capabilities using Python, working closely with cross-functional teams to deliver scalable and robust solutions. The engineer will focus on building and maintaining core components of the IDP platform, contributing to the product roadmap and exploring the latest AI technologies.
As a Senior Software Engineer in Medtronic's AI and Data Science Platform team, you will design, build, and maintain software solutions that enable machine learning engineers and data scientists to develop new products. You will work on a SaaS tool for project, data, and annotation management, collaborate with data and platform engineers, and ensure high-quality, scalable software delivery.
This role involves prototyping and developing innovative cybersecurity solutions using AI, with a focus on enhancing Darktrace’s platform to detect and respond to unknown threats. You’ll work in a cross-functional R&D team, balancing creative exploration with structured development of scalable features. The position emphasizes ownership of novel projects, collaboration, and advancing core capabilities in Python and containerized environments.
Design and build production-grade, AI-driven systems with a focus on safety, compliance, and scalability in regulated financial environments. Develop policy enforcement, behavioural monitoring, and evaluation frameworks for agentic AI workflows on a serverless AWS platform. Collaborate with AI, product, and compliance teams while mentoring engineers and shaping best practices in AI-augmented development.
This role involves designing, developing, testing, and maintaining robust software applications using Python and AI technologies. You will work with generative AI tools, provide technical guidance, and ensure compliance with security policies. The position offers the opportunity to influence digital innovation and shape the University's technology landscape.
Build and maintain a high-performance backend platform for AI-driven, multi-physics simulation used by data and simulation engineers. Work on scalable, observable systems in Python and Go, with ownership from development to production. Collaborate closely with domain experts in engineering and machine learning to enable physics-informed model deployment across aerospace, energy, and advanced manufacturing sectors.
Develop AI-driven video processing solutions within a deep tech environment, focusing on scalable media delivery and real-time systems. Work with Python and modern cloud infrastructure, integrating AI and video technologies to enhance content delivery. Collaborate on building maintainable, tested software for immersive media platforms.
This role involves building production applications and APIs using Python and FastAPI, developing LLM, RAG, and AI agent solutions, and working with vector databases. You'll collaborate with engineers, architects, and client stakeholders to take GenAI POCs into production and scale them.
This role involves developing and maintaining data pipelines, building a data warehouse or lakehouse architecture, and ensuring data accuracy and governance. You will collaborate with engineers and business stakeholders to make data accessible and useful, and prepare the platform for future analytics and AI applications.
This role involves designing and developing AI-powered applications and machine learning solutions using Python and modern AI frameworks. You will take solutions from concept to deployment, ensuring they meet enterprise production standards, and collaborate with technical teams and business stakeholders to identify opportunities for AI adoption.
This role involves designing and implementing core components of the JAX framework to optimize performance on NVIDIA's AI platforms, particularly for deep learning workloads. The engineer will collaborate with AI researchers and architects to bridge cutting-edge numerical computing research with real-world applications. Key responsibilities include enhancing JAX's modularity, improving execution speed, and building tools that boost developer efficiency across distributed GPU environments.
